A 30+ Year AVHRR Land Surface Reflectance Climate Data Record and Its Application to Wheat Yield Monitoring
| Autor: | Inbal Becker-Reshef, Martin Claverie, Belen Franch, Sadashiva Devadiga, Jyoteshwar Nagol, Frédéric Baret, D. Meyer, Jean-Claude Roger, Eric Vermote, Emilie Murphy, Robert E. Wolfe, Christopher O. Justice, Ivan Csiszar, Edward J. Masuoka |
|---|---|
| Přispěvatelé: | Department of Geographical Sciences [College Park], University of Maryland [College Park], University of Maryland System-University of Maryland System, NASA Goddard Space Flight Center (GSFC), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Department of Geographical Sciences, NOAA Center for Satellite Applications and Research (STAR), NOAA National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Science Systems and Applications Inc (SSAI), NOAA NCEI NA14NES432003 |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
ble tendre
010504 meteorology & atmospheric sciences reflectance Advanced very-high-resolution radiometer télédétection [SDE.MCG]Environmental Sciences/Global Changes 0211 other engineering and technologies 02 engineering and technology Land cover radiomètre 01 natural sciences Normalized Difference Vegetation Index Article remote sensing Calibration surface reflectance yield monitoring radiométrie haute resolution Leaf area index analyse de rendement Milieux et Changements globaux lcsh:Science global change ComputingMilieux_MISCELLANEOUS 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing AVHRR [PHYS]Physics [physics] surface reflectance changement climatique Radiometer yield monitoring radiometer AERONET soft wheat MODIS 13. Climate action [SDE]Environmental Sciences LCDR rendement agricole General Earth and Planetary Sciences Environmental science lcsh:Q Moderate-resolution imaging spectroradiometer |
| Zdroj: | Remote Sensing Remote Sensing, MDPI, 2017, 9 (3), pp.296. ⟨10.3390/rs9030296⟩ Remote Sensing, MDPI, 2017, 9 (3), ⟨10.3390/rs9030296⟩ Remote Sensing, Vol 9, Iss 3, p 296 (2017) Volume 9 Issue 3 Pages: 296 Remote sensing Remote Sensing 3 (9), . (2017) Remote Sensing, 2017, 9 (3), pp.296. ⟨10.3390/rs9030296⟩ |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs9030296⟩ |
| Popis: | The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980s to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR surface reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geolocation, improvement of cloud masking, and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream leaf area index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by Becker-Reshef et al. (2010) and Franch et al. (2015) are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980s, the results have errors equivalent to those derived from MODIS. |
| Databáze: | OpenAIRE |
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